class_docstr: A Fake in-process executor what returns execution result.
code: def Do(
      self,
      input_dict: Dict[str, List[types.Artifact]],
      output_dict: Dict[str, List[types.Artifact]],
      exec_properties: Dict[str, Any],
  ) -> execution_result_pb2.ExecutorOutput:
      executor_output = execution_result_pb2.ExecutorOutput()
      outputs_utils.populate_output_artifact(
          executor_output, output_dict
      )
      outputs_utils.populate_exec_properties(
          executor_output, exec_properties
      )
      return executor_output
  
imports: import os
  from typing import Any, Dict, List
  import tensorflow
  from tfx import types
  from tfx.dsl.components.base import base_executor
  from tfx.dsl.io import fileio
  from tfx.orchestration.portable import data_types
  from tfx.orchestration.portable import outputs_utils
  from tfx.orchestration.portable import python_executor_operator
  from tfx.proto.orchestration import executable_spec_pb2
  from tfx.proto.orchestration import execution_result_pb2
  from tfx.proto.orchestration import pipeline_pb2
  from tfx.types import standard_artifacts
  from tfx.utils import test_case_utils
  from google.protobuf import text_format
label_desc: Use image node_id 1 for calling the InprocessExecutor obj's underlying member method code with example usage: obj.Do(input_dict, output_dict, exec_properties) and returns: executor_output